The present invention relates to speech recognition computers, and more particularly to speaker independent recognition computers. Specifically, this invention relates to a microcomputer used for speaker independent speech recognition with a carefully selected vocabulary which may be manufactured at extremely low cost for specialized applications.
Use of computers to recognize human speech has developed over the last 30 years to provide increasingly complex computerized systems capable of recognizing increasing vocabularies. In addition, substantial effort has been devoted toward the goal of speaker independent recognition systems.
Virtually all of the serious work in speech recognition systems has been based upon a spectral analysis of the incoming voice signals through the use of a bank of band pass filters, each selecting a different frequency band, as a system front end. The signal levels or voice power in each of the band pass filter ranges has typically been sampled at periodic time intervals to provide a frequency vs. time speech matrix for words or phrases. A variety of time normalization techniques have been utilized to recognize words regardless of their time duration, and frequency normalization techniques have been used in attempts to achieve speaker independence.
All of this development, of course, has generated increasingly complex and expensive equipment, placing the advantages of speech recognition beyond the price range for most consumer products. In essence, speech recognition computers have been limited to laboratory tools and input systems for complex equipment, systems having a high enough cost to justify the expense of complicated speech recognition systems as an input medium.
With this development, the utility of a simplified speech recognition device for a variety of consumer products has been overlooked. Furthermore, the techniques utilized for more complex systems do not lend themselves to relatively simple speech recognition systems, since the storage requirements alone for most recognition systems is so substantial that the cost of the memory itself places the systems beyond the reach of the consumer market.
While other systems have recognized the utility of spectral analysis for speech recognition, these systems have attempted to discern relatively similar elements of speech, such as the vowels U and O and the plosives T and B, in order to broaden the system vocabulary.